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fix heatmap tiling after linalg refactor #266

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Merged
kushalkolar merged 4 commits into from
Jul 6, 2023
Merged

fix heatmap tiling after linalg refactor #266

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1d1be84
fix heatmap tiling after linalg refactor
kushalkolar Jun 29, 2023
5ef8d76
I can't even do a simple fix properly
kushalkolar Jun 29, 2023
eb0a444
simpler nb example
kushalkolar Jun 30, 2023
35be10a
change heatmap example nb
kushalkolar Jul 5, 2023
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53 changes: 14 additions & 39 deletions examples/notebooks/heatmap.ipynb
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Original file line number Diff line number Diff line change
Expand Up @@ -20,17 +20,15 @@
"outputs": [],
"source": [
"import numpy as np\n",
"import fastplotlib as fpl\n",
"\n",
"from tqdm import tqdm"
"import fastplotlib as fpl"
]
},
{
"cell_type": "markdown",
"id": "908f93f8-68c3-4a36-8f40-e0aab560955d",
"metadata": {},
"source": [
"## Generate some random neural-like data"
"## Generate some sine and cosine data"
]
},
{
Expand All @@ -42,70 +40,47 @@
},
"outputs": [],
"source": [
"def generate_traces(n_components, n_frames):\n",
" n_frames = n_frames + 50\n",
" n_components = n_components\n",
" \n",
" out = np.zeros((n_components, n_frames), dtype=np.float16)\n",
" \n",
" xs = np.arange(0, 50, 1)\n",
" # exponential decay\n",
" _lambda = 0.1\n",
" ys = np.e**-(_lambda * xs)\n",
" \n",
" for component_num in tqdm(range(n_components)):\n",
" time_step = 0\n",
" while time_step < n_frames - 50:\n",
" firing_prop = np.random.randint(0, 20)\n",
" if np.random.poisson() > firing_prop:\n",
" out[component_num, time_step:min(time_step + 50, n_frames - 1)] = ys.astype(np.float16)\n",
" time_step += 100\n",
" else:\n",
" time_step += 2\n",
" \n",
" return out[:, :n_frames - 50]"
]
},
{
"cell_type": "markdown",
"id": "fc1070d9-f9e9-405f-939c-a130cc5c456a",
"metadata": {},
"source": [
"Generate an array that is `10,000 x 30,000`, this may take a few minutes"
"xs = np.linspace(0, 50, 10_000)\n",
"\n",
"sine_data = np.sin(xs)\n",
"\n",
"cosine_data = np.cos(xs)\n",
"\n",
"data = np.vstack([(sine_data, cosine_data) for i in range(5)])"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "8a1b83f6-c0d8-4237-abd6-b483e7d978ee",
"id": "02b072eb-2909-40c8-8739-950f07efbbc2",
"metadata": {
"tags": []
},
"outputs": [],
"source": [
"temporal = generate_traces(10_000, 30_000)"
"data.shape"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "f89bd740-7397-43e7-9e66-d6cfb14de884",
"id": "84deb31b-5464-4cce-a938-694371011021",
"metadata": {
"tags": []
},
"outputs": [],
"source": [
"plot = fpl.Plot()\n",
"\n",
"plot.add_heatmap(temporal, cmap=\"viridis\")\n",
"plot.add_heatmap(data, cmap=\"viridis\")\n",
"\n",
"plot.show(maintain_aspect=False)"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "84deb31b-5464-4cce-a938-694371011021",
"id": "df3f8994-0f5b-4578-a36d-4cd9bf0733c0",
"metadata": {},
"outputs": [],
"source": []
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4 changes: 2 additions & 2 deletions fastplotlib/graphics/image.py
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Original file line number Diff line number Diff line change
Expand Up @@ -500,8 +500,8 @@ def __init__(
img.row_chunk_index = chunk[0]
img.col_chunk_index = chunk[1]

img.position_x = x_pos
img.position_y = y_pos
img.world.x = x_pos
img.world.y = y_pos

self.world_object.add(img)

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